This second issue of volume 9 (2019) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: the correspondence analysis on a generalized aggregated lexical table (CA-GALT); new univariate and bivariate statistics for distributional variables in the framework of symbolic data analysis; the selection of a number of clusters that not only fits well the data, but simultaneously uses the potential illustrative ability of the available external variables in the model-based clustering context; a mixture model averaging for clustering; a simple nonlinear biplot that represents the marker points of a variable on a curved line that is governed by splines.

Editorial for issue 2/2015 / Bock, Hh; Gaul, W; Okada, A; Vichi, M; Weihs, C. - In: ADVANCES IN DATA ANALYSIS AND CLASSIFICATION. - ISSN 1862-5347. - 9:2(2015), pp. 121-123. [10.1007/s11634-015-0207-9]

Editorial for issue 2/2015

Vichi, M
;
2015

Abstract

This second issue of volume 9 (2019) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: the correspondence analysis on a generalized aggregated lexical table (CA-GALT); new univariate and bivariate statistics for distributional variables in the framework of symbolic data analysis; the selection of a number of clusters that not only fits well the data, but simultaneously uses the potential illustrative ability of the available external variables in the model-based clustering context; a mixture model averaging for clustering; a simple nonlinear biplot that represents the marker points of a variable on a curved line that is governed by splines.
2015
Classification, Clustering, Data Analysis
01 Pubblicazione su rivista::01m Editorial/Introduzione in rivista
Editorial for issue 2/2015 / Bock, Hh; Gaul, W; Okada, A; Vichi, M; Weihs, C. - In: ADVANCES IN DATA ANALYSIS AND CLASSIFICATION. - ISSN 1862-5347. - 9:2(2015), pp. 121-123. [10.1007/s11634-015-0207-9]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1670616
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